Method and system for constructing a port group iron ore transportation network chain and planning optimization of resilience with intelligent decision fusion

Abstract

The application discloses a kind of port group iron ore transport network chain construction and flexibility planning optimization method and system of fusion intelligent decision, it is related to port planning technical field, this method includes: all ports between the starting place to destination of iron ore transport are mapped as port node, the passage between the port node is mapped as edge, constitute multiple the transport network chain between the starting place to the destination;According to the whole process transport timeliness of each transport network chain, network chain disturbance occurrence rate and transport capacity utilization, each transport network chain is divided into core transport network chain or backup transport network chain, and the flexibility value of each backup transport network chain is calculated, wherein, the core transport network chain is preferentially selected for iron ore transport;When the core transport network chain is disturbed by network chain, the disturbance comprehensive quantitative value of the disturbance is calculated, whether the backup transport network chain is enabled is judged, if enabled, according to the flexibility value, the corresponding backup transport network chain is selected.

Description

Technical Field

[0001] This invention belongs to the field of port planning technology, and in particular relates to a method and system for constructing and optimizing the resilience planning of port cluster iron ore transportation network chains that integrates intelligent decision-making. Background Technology

[0002] Existing technologies generally adopt a rigid network layout of "single hub - single channel - single destination," lacking a systematic approach to collaboratively constructing multiple transportation network chains, resulting in extremely weak network resilience. Specifically, existing planning methods optimize only a single port or transportation channel independently, with independent routes and node resources between ports and isolated information, lacking a collaborative scheduling mechanism across ports and channels. Furthermore, there is a lack of functional division among different port nodes in the network, and no method for functional hierarchy based on quantitative indicators exists between core hub ports and regional transshipment ports, leading to ambiguous port positioning, overlapping functions, and a pattern of homogeneous competition rather than collaborative complementarity. More importantly, existing technologies lack a dual-track network structure design of "core network chain + backup network chain." If the core transportation channel is interrupted due to extreme weather, port closures, or waterway disruptions, there are no redundant transportation paths within the system that can be immediately resumed. This capacity vacuum is directly transmitted to steel mills in the hinterland, causing raw material supply disruptions and compromising the overall robustness of the supply chain.

[0003] Existing multi-route planning technologies merely add backup routes, failing to deeply integrate route design with the functional divisions of port clusters and the differentiated needs of steel mills, resulting in severe misallocation of transportation resources. Current solutions, when adding backup routes, typically optimize based on geographical distance or single transportation cost, ignoring fundamental differences in technical dimensions such as ocean handling capacity, the number of intermodal connections, transshipment timeliness, and feeder distribution coverage among ports with different functions. This leads to a lack of quantitatively defined functional distinctions between high-efficiency direct networks and high-resilience bypass networks. Simultaneously, existing technologies lack a method to integrate route timeliness adaptability, capacity consumption constraint compliance, route resilience adaptability, functional adaptability, and demand adaptability into a unified evaluation framework. This prevents simultaneous verification of route feasibility from both the route's technical performance and its ability to meet the actual needs of steel mills. Consequently, while planned routes may be geographically feasible, they exhibit systemic deviations in functional fit, category coverage, and timeliness demand matching, resulting in high resource idle rates and persistently low network utilization in actual operation.

[0004] Existing resilience planning methods are primarily qualitative, lacking an executable quantitative assessment index system and a real-time dynamic decision-making mechanism. This results in an inability to quickly and accurately select the optimal response strategy when disturbances occur. While existing research has proposed conceptual frameworks for resilience, such as disturbance resistance and recovery, it has not established a complete quantitative parameter system covering four technical dimensions: disturbance resistance performance, interruption recovery timeliness, dynamic allocation performance, and iterative optimization efficiency. It cannot convert key technical indicators such as network robustness, node redundancy, channel disturbance resistance, recovery timeliness, and emergency response efficiency into calculable and comparable values. Furthermore, existing technologies lack a comprehensive quantitative method for disturbance levels. After a disturbance occurs, the severity is judged solely based on experience, failing to calculate a standardized comprehensive disturbance score based on multi-dimensional measured data such as disturbance duration, number of affected channels, cargo flow delays, and efficiency loss rates. Consequently, it is impossible to formulate differentiated capacity allocation plans corresponding to disturbance levels, resulting in severely insufficient real-time and accuracy in disturbance response decisions. This often leads to delayed responses under major disturbances and complete loss of control under extreme disturbances.

[0005] Therefore, a technical solution is urgently needed to solve the above technical problems. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention proposes a method for constructing and optimizing the resilience planning of a port cluster iron ore transportation network chain that integrates intelligent decision-making, comprising: All ports between the origin and destination of iron ore transportation are mapped as port nodes, and the channels between the port nodes are mapped as edges, forming multiple transportation network chains between the origin and the destination. Based on the overall transportation time, disturbance rate, and capacity utilization rate of each transportation network chain, each transportation network chain is divided into a core transportation network chain or a backup transportation network chain, and the resilience value of each backup transportation network chain is calculated. Among these, the core transportation network chain is preferentially selected for iron ore transportation. When the core transport network chain is disturbed, the comprehensive quantification value of the disturbance is calculated to determine whether the backup transport network chain should be activated. If activated, the corresponding backup transport network chain is selected based on the resilience value.

[0007] Furthermore, before forming multiple transportation network chains from the origin to the destination, the method further includes: dividing each port node into a core hub port node, a regional transshipment port node, or a feeder port node. Each transportation network chain includes the core hub port node, the regional transshipment port node, and the feeder port node. Multiple evaluation indicators are set for each port node, normalized, and weights are assigned to each evaluation indicator to calculate the comprehensive evaluation value of each port node. The evaluation indicators include: an unloading scale indicator represented by the annual iron ore ocean-going vessel unloading volume; an intermodal transport suitability indicator represented by the ratio of intermodal transshipment cargo to the port's total annual iron ore transshipment volume; a transshipment timeliness indicator represented by the average iron ore transshipment time; a feeder capacity indicator represented by the annual feeder vessel unloading volume; and a delivery coverage indicator represented by the short-distance delivery radius.

[0008] Furthermore, calculating the comprehensive evaluation value for each of the port nodes includes: in, For the first The comprehensive evaluation value of each of the aforementioned port nodes, For the first The first port node The aforementioned evaluation indicators, For the first The first port node The weights of the evaluation indicators; when When the value is greater than or equal to the first evaluation threshold, the first value will be... The aforementioned port nodes are divided into the core hub port nodes, when When the value is less than the first evaluation threshold and greater than or equal to the second evaluation threshold, the first evaluation threshold will be... The aforementioned port nodes are divided into transit port nodes in the region, when When it is less than the second evaluation threshold, the first The port nodes are divided into the feed port nodes.

[0009] Furthermore, after forming multiple transport network chains between the origin and the destination, the process further includes: determining the number of transport network chains. in, The number of the transport network chains, This represents the total annual iron ore transport volume for all the aforementioned port nodes. For the first The maximum cargo flow carrying capacity of the aforementioned transportation network chain.

[0010] Furthermore, based on the overall transportation timeliness, network disturbance rate, and capacity utilization rate of each transportation network chain, classifying each transportation network chain into a core transportation network chain or a backup transportation network chain includes: designating transportation network chains with a capacity utilization rate greater than or equal to a capacity utilization rate threshold as candidate core transportation network chains, and designating transportation network chains with a capacity utilization rate less than the capacity utilization rate threshold as candidate backup transportation network chains; If the overall transportation time of the candidate core transportation network chain is less than or equal to a first threshold for overall transportation time, and the network chain disturbance rate is less than or equal to a first threshold for network chain disturbance rate, then it is classified as the core transportation network chain; otherwise, it is classified as the backup transportation network chain. If the overall transportation time of the candidate backup transportation network chain is less than or equal to a second threshold for overall transportation time, the network chain disturbance rate is less than or equal to a second threshold for network chain disturbance rate, and the average time required for the candidate backup transportation network chain to recover to a preset percentage of its rated capacity after activation is less than or equal to a recovery time threshold, then the candidate backup transportation network chain is designated as the backup transportation network chain; otherwise, it is re-planned.

[0011] Furthermore, calculating the resilience value of each of the backup transport network chains includes: in, The toughness value, As the first weight, The weights are used to measure the robustness of the network. The robustness value of the backup transport network chain is given. As the weight of redundancy, This refers to the redundancy of core port nodes in the backup transportation network. As the weight of the channel immunity, This refers to the channel immunity of the channels between the port nodes in the backup transportation network chain. As the second weight, To restore the weight of the timeliness value, To restore the validity period, Weights for restoring efficiency, To restore efficiency, As a weight for emergency response efficiency, To improve emergency response efficiency, As the third weight, Weights for path switching adaptability. For path switching adaptability, Weighting of the response accuracy of capacity allocation To improve the accuracy of capacity allocation response, The weighting of capacity loss rate to maintain resilience To maintain resilience and reduce capacity loss rates, As the fourth weight, As a weight for resilience iteration efficiency, For resilient iteration efficiency, The weight of the perturbation experience utilization rate, To improve the utilization rate of perturbation experience, As a weight for the improvement rate of toughness assessment accuracy, To improve the accuracy of toughness assessment.

[0012] Furthermore, calculating the comprehensive quantization value of the network chain disturbance includes: in, The comprehensive quantization value of the disturbance is... For the first The weight of each perturbation quantization value For the first A disturbance quantification value, the disturbance quantification value includes: a quantification value of the duration of the disturbance, a quantification value of the number of transportation channels affected, a quantification value of the amount of cargo flow delay, or a quantification value of the efficiency loss rate; Determining whether to activate the backup transport network chain includes: when If the disturbance value is less than the first disturbance threshold, the disturbance is considered a general disturbance, and only the capacity of the corresponding port node in the core transportation network is adjusted. If the disturbance threshold is greater than or equal to the first disturbance threshold and less than the second disturbance threshold, then the network chain disturbance is a major disturbance, and the core transport network chain is switched to the backup transport network chain. If the disturbance is greater than or equal to the second disturbance threshold, then the disturbance in the network chain is an extreme disturbance, and all the backup transport network chains are activated for coordinated operation.

[0013] Furthermore, selecting the corresponding backup transport network chain based on the resilience value includes: in, This is a toughness correction value. The toughness value, The weight of the toughness value, The adaptation evaluation value for the backup transport network chain; When the disturbance in the network chain is a major disturbance, the core transport network chain is switched to the backup transport network chain corresponding to the largest resilience correction value among all the backup transport network chains.

[0014] Furthermore, when the network disturbance is an extreme disturbance, capacity is allocated to each of the backup transport network chains, including: in, For the first The capacity allocation of the aforementioned backup transport network chain. This refers to the total transport capacity that needs to be diverted from the core transport network when the network disturbance occurs. For the first The weight of each of the aforementioned backup transport network chains, For the first The average channel immunity of the aforementioned backup transport network chain, For the first The weight of each of the aforementioned backup transport network chains, For the first The average channel immunity of each of the aforementioned backup transport network chains.

[0015] This invention also proposes a port cluster iron ore transportation network construction and resilience planning optimization system integrating intelligent decision-making, including: The networking module is used to map all ports between the origin and destination of iron ore transportation as port nodes, and the channels between the port nodes are mapped as edges, forming multiple transportation network chains between the origin and the destination. The network chain segmentation module is used to divide each of the transport networks into core transport networks or backup transport networks based on the overall transport time, network chain disturbance rate and capacity utilization rate of each transport network, and to calculate the resilience value of each backup transport network. Among these, the core transport networks are preferentially selected for iron ore transport. The control module is used to calculate the comprehensive quantification value of the disturbance when the core transport network chain is disturbed, determine whether to activate the backup transport network chain, and select the corresponding backup transport network chain according to the resilience value if activated.

[0016] Compared with the prior art, the present invention has the following advantages and technical effects: This invention, through the collaborative construction of multiple transportation network chains based on the quantitative division of port functions, transforms port clusters from independent "island-style" single-channel layouts into a dual-track network chain system with redundancy backup and collaborative scheduling capabilities. This fundamentally eliminates the structural vulnerability of supply chain disruption caused by a single point interruption in the core channel, significantly improving the overall robustness of the transportation network. When disturbances occur, the invention can quickly determine the disturbance level based on measured data and accurately select the optimal backup network chain, overcoming the problems of existing technologies that rely on experience-based judgment for disturbance response, resulting in delayed decision-making and insufficient accuracy. Attached Figure Description

[0017] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart of the method in Embodiment 1 of the present invention; Figure 2 This is a system structure diagram of Embodiment 2 of the present invention. Detailed Implementation

[0018] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0019] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0020] Example 1 like Figure 1 As shown in the figure, this embodiment proposes a method for constructing and optimizing the resilience planning of a port cluster iron ore transportation network chain that integrates intelligent decision-making, specifically including the following steps: Step S1: Map all ports between the origin and destination of iron ore transportation as port nodes, and map the channels between the port nodes as edges to form multiple transportation network chains between the origin and the destination. Specifically, before forming multiple transportation networks from the origin to the destination, the process further includes: dividing each port node into a core hub port node, a regional transshipment port node, or a feeder port node. Each transportation network includes the core hub port node, the regional transshipment port node, and the feeder port node. Multiple evaluation indicators are set for each port node, normalized, and weights are assigned to each indicator to calculate a comprehensive evaluation value for each port node. The evaluation indicators include: an unloading scale indicator represented by the annual iron ore ocean-going vessel unloading volume; an intermodal transport suitability indicator represented by the ratio of intermodal transshipment cargo to the port's total annual iron ore transshipment volume; a transshipment timeliness indicator represented by the average iron ore transshipment time; a feeder capacity indicator represented by the annual feeder vessel unloading volume; and a delivery coverage indicator represented by the short-distance delivery radius.

[0021] For example, each of the aforementioned transport network chains may include one core hub port node, two to three regional transshipment port nodes, and three to four feeder port nodes.

[0022] Specifically, calculating the comprehensive evaluation value for each of the port nodes includes: in, For the first The comprehensive evaluation value of each of the aforementioned port nodes, For the first The first port node The aforementioned evaluation indicators, For the first The first port node The weights of the evaluation indicators; when When the value is greater than or equal to the first evaluation threshold, the first value will be... The aforementioned port nodes are divided into the core hub port nodes, when When the value is less than the first evaluation threshold and greater than or equal to the second evaluation threshold, the first evaluation threshold will be... The aforementioned port nodes are divided into transit port nodes in the region, when When it is less than the second evaluation threshold, the first The port nodes are divided into the feed port nodes.

[0023] For example, when ≥85, the first The aforementioned port nodes are divided into the core hub port nodes, when 65≤ <85, the first The aforementioned port nodes are divided into transit port nodes in the region, when <65, the first The port nodes are divided into the feed port nodes.

[0024] Specifically, after forming multiple transport network chains between the origin and the destination, the process further includes: determining the number of transport network chains. in, The number of the transport network chains, This represents the total annual iron ore transport volume for all the aforementioned port nodes. For the first The maximum cargo flow carrying capacity of the aforementioned transportation network chain.

[0025] Step S2: Based on the overall transportation time, chain disturbance rate, and capacity utilization rate of each transportation chain, divide each transportation chain into a core transportation chain or a backup transportation chain, and calculate the resilience value of each backup transportation chain. Among these, the core transportation chain is preferentially selected for iron ore transportation. Specifically, based on the overall transportation timeliness, network disturbance rate, and capacity utilization rate of each transportation network chain, classifying each transportation network chain into a core transportation network chain or a backup transportation network chain includes: designating transportation network chains with a capacity utilization rate greater than or equal to a capacity utilization rate threshold (e.g., 75%) as candidate core transportation network chains, and designating transportation network chains with a capacity utilization rate less than the capacity utilization rate threshold as candidate backup transportation network chains; If the overall transportation time of the candidate core transportation network chain is less than or equal to the first threshold for overall transportation time (e.g., 72 hours), and the network chain disturbance rate is less than or equal to the first threshold for network chain disturbance rate (e.g., 5%), then it is designated as the core transportation network chain; otherwise, it is designated as the backup transportation network chain. If the overall transportation time of the candidate backup transportation network chain is less than or equal to the second threshold for overall transportation time (e.g., 120 hours), the network chain disturbance rate is less than or equal to the second threshold for network chain disturbance rate (e.g., 3%), and the average time required for the candidate backup transportation network chain to recover to a preset percentage of its rated capacity after activation is less than or equal to the recovery time threshold (e.g., 48 hours), then the candidate backup transportation network chain is designated as the backup transportation network chain; otherwise, it is replanned.

[0026] Specifically, calculating the resilience value of each of the backup transport network chains includes: in, The toughness value, As the first weight, The weights are used to measure the robustness of the network. The robustness value of the backup transport network chain is given. As the weight of redundancy, This refers to the redundancy of core port nodes in the backup transportation network. As the weight of the channel immunity, This refers to the channel immunity of the channels between the port nodes in the backup transportation network chain. As the second weight, To restore the weight of the timeliness value, To restore the validity period, Weights for restoring efficiency, To restore efficiency, As a weight for emergency response efficiency, To improve emergency response efficiency, As the third weight, Weights for path switching adaptability. For path switching adaptability, Weighting of the response accuracy of capacity allocation To improve the accuracy of capacity allocation response, The weighting of capacity loss rate to maintain resilience To maintain resilience and reduce capacity loss rates, As the fourth weight, As a weight for resilience iteration efficiency, For resilient iteration efficiency, The weight of the perturbation experience utilization rate, To improve the utilization rate of perturbation experience, As a weight for the improvement rate of toughness assessment accuracy, To improve the accuracy of toughness assessment.

[0027] Preferably, Normalize to [0,1], then adjust according to high toughness ( ≥0.8), medium toughness ( Belongs to [0.5, 0.8)), low toughness ( <0.5) is used for three-level classification. In addition, it should be noted that this embodiment not only calculates the backup transport network chain. All transport network chains can be calculated. .

[0028] Preferably, in this embodiment, the ST-CNN model is used to... Iterative prediction is performed, using historical data of port nodes and historical traffic capacity data of channels as spatiotemporal feature inputs, ultimately completing the prediction. The prediction.

[0029] Preferably, this embodiment provides a calculation The specific method is as follows: in, This refers to the number of remaining effective transport links after a core port node or channel is interrupted. This represents the total number of transport links when the backup transport network is operating normally.

[0030] calculate The specific method is as follows: in, This represents the number of backup nodes corresponding to the core port nodes. This represents the total number of core nodes in the backup transportation network chain.

[0031] calculate The specific method is as follows: in, For the first The average duration of channel interruption caused by network-like disturbances. For the first The annual frequency of network-like disturbances The total duration of the statistical period. This represents the total frequency of network link disturbances within the statistical period. This represents the number of network disturbance types.

[0032] calculate The specific method is as follows: in, This refers to the average recovery time of the alternative transport chain after a chain disturbance. This is the preset maximum acceptable recovery time.

[0033] calculate The specific method is as follows: in, To restore the actual capacity of the backup transportation network, This is the normal rated capacity of the backup transport network.

[0034] calculate The specific method is as follows: in, This refers to the actual response time after the linkage rule is triggered. Preset emergency response time limits.

[0035] calculate The specific method is as follows: in, The adaptation assessment value for the backup transport network chain. The adaptation assessment value for the core transportation network chain.

[0036] calculate The specific method is as follows: in, This is an adjustment to the actual transport capacity. Adjustments to capacity demand.

[0037] calculate The specific method is as follows: in, To ensure the availability of backup transport network links with actual capacity after implementing resilience enhancement measures (such as adding redundant port nodes and optimizing channels), This is the normal rated capacity of the backup transport network.

[0038] calculate The specific method is as follows: in, This is the resilience value (i.e., resilience correction value) of the updated backup transport network chain. The resilience value of the backup transport network chain before the update. For the update cycle.

[0039] calculate The specific method is as follows: in, This represents the number of port nodes in the backup transport network, which has been optimized to account for historical network disturbances. This represents the total number of historical network disturbances.

[0040] calculate The specific method is as follows: in, To assess the prediction accuracy of the ST-CNN model when evaluating the resilience of backup transportation network chains, This is the baseline prediction accuracy when using traditional methods (such as single statistical regression) to assess the resilience of backup transportation network chains.

[0041] Preferably, regarding core port nodes, firstly calculate the node degree and betweenness centrality of each port node in the core transport network chain or the backup transport network chain, and designate port nodes whose node degree exceeds the node degree threshold and whose betweenness centrality exceeds the betweenness centrality threshold as core port nodes.

[0042] Step S3: When the core transport network chain is disturbed by the network chain, calculate the comprehensive quantification value of the disturbance and determine whether to activate the backup transport network chain. If activated, select the corresponding backup transport network chain according to the resilience value.

[0043] Specifically, calculating the comprehensive quantization value of the network chain disturbance includes: in, The comprehensive quantization value of the disturbance is... For the first The weight of each perturbation quantization value For the first A disturbance quantification value, the disturbance quantification value includes: a quantification value of the duration of the disturbance, a quantification value of the number of transportation channels affected, a quantification value of the amount of cargo flow delay, or a quantification value of the efficiency loss rate; Determining whether to activate the backup transport network chain (i.e., the linkage rule) includes: when If the disturbance value is less than the first disturbance threshold, the disturbance is considered a general disturbance, and only the capacity of the corresponding port node in the core transportation network is adjusted. If the disturbance threshold is greater than or equal to the first disturbance threshold and less than the second disturbance threshold, then the network chain disturbance is a major disturbance, and the core transport network chain is switched to the backup transport network chain. If the disturbance is greater than or equal to the second disturbance threshold, then the disturbance in the network chain is an extreme disturbance, and all the backup transport network chains are activated for coordinated operation.

[0044] For example, when If 30 < 30, then the network disturbance is a general disturbance; if 30 ≤ If <70, then the network disturbance is a major disturbance; when extreme If the value is ≥70, then the network disturbance is an extreme disturbance.

[0045] Preferably, the quantized value for calculating the duration of the disturbance is... include: in, The duration of the disturbance caused by the network chain disturbance.

[0046] Calculate the quantitative value affecting the number of transport corridors include: in, The number of channels affected by network chain disturbances. This represents the total number of channels.

[0047] Quantitative values ​​for calculating freight flow delays include: in, The amount of cargo delays caused by network disruptions. This is the normal rated capacity of the core transportation network chain.

[0048] Quantitative value of performance loss rate include: in, The benchmark value for comprehensive performance ( ,in, This represents the actual daily transport volume before the network disruption occurred. (for the entire transportation time) This represents the measured overall performance value.

[0049] Specifically, selecting the corresponding backup transport network chain based on the resilience value includes: in, This is a toughness correction value. The toughness value, The weight of the toughness value (for example, It can be 0.7). This is the adaptation evaluation value for the backup transport network chain. Additionally, it should be noted that this embodiment not only calculates the backup transport network chain... All transport network chains can be calculated. All transport networks can also be calculated. ; When the disturbance in the network chain is a major disturbance, the core transport network chain is switched to the backup transport network chain corresponding to the largest resilience correction value among all the backup transport network chains.

[0050] Preferably, this embodiment provides the following method for calculating the adaptation evaluation value of the backup transport network chain. : in, The weights for the first adaptation dimension. For the backup transport network chain, the first The first adaptation dimension of the port node is the... One adaptation metric, The weights for the second adaptation dimension. For the backup transport network chain, the first The second adaptation dimension of the port node is the first One adaptation metric, The weights for the third adaptation dimension. The third adaptation dimension of the backup transport network chain One matching metric.

[0051] The backup transport network chain in the first The first adaptation dimension of the port node is the... Adaptation metrics Including: the Port adaptability of the aforementioned port nodes Node resource adaptability or intermodal connectivity , where, calculate the first Port adaptability of the aforementioned port nodes include: in, For the first The evaluation threshold for the nth port node, for example, if the nth... If the aforementioned port nodes are the core hub port nodes, then The first evaluation value threshold is used if the first... If each of the aforementioned port nodes is a transit port node in the region, then As the second evaluation threshold, if the first If each of the aforementioned port nodes is a feeding port node, then For values ​​less than the second evaluation threshold, when When the value is greater than 1, take 1.

[0052] Calculate the first Node resource adaptability of the aforementioned port nodes include: in, For the first The actual annual iron ore processing capacity of each of the aforementioned port nodes. For the first The required iron ore throughput of each of the port nodes in the backup transport network.

[0053] Calculate the first Intermodal connectivity of the aforementioned port nodes include: in, For the first The number of possible combinations of transportation modes that can be connected to the port node (for example, combinations of transportation modes can be "sea-rail", "sea-river", etc.). For the first The number of transport mode combinations required for each of the aforementioned port nodes.

[0054] The backup transport network chain in the first The second adaptation dimension of the port node is the first Adaptation metrics Including: the Path timeliness adaptation of the aforementioned port nodes Path capacity consumption constraint fit or path resilience adaptability , where, calculate the first Path timeliness adaptation of the aforementioned port nodes include: in, For the first The channel occupancy time thresholds set for each port node are as follows: core hub port node ≤ 72 hours, regional transshipment port node ≤ 96 hours, and feeder port node ≤ 48 hours. For the first The actual channel occupancy time of each of the aforementioned port nodes.

[0055] Calculate the first The fit of the path capacity consumption constraints of the port nodes mentioned above include: in, For the first The actual capacity allocation of each of the aforementioned port nodes. For the first The maximum capacity of each of the aforementioned port nodes.

[0056] Calculate the first Path resilience adaptability of the port nodes include: in, For the first The first port node The proportion of cargo traffic handled by each channel to the total cargo traffic of the backup transport network chain. For the first The first port node Channel immunity of each channel.

[0057] The third adaptation dimension of the backup transport network chain Adaptation metrics Including: Category compatibility Adaptability to timeliness requirements Or dosage suitability Among them, calculating category suitability include: in, This refers to the quantity of iron ore types that the backup transport network can transport and that meet the steel mill's needs. This represents the total quantity of different types of iron ore required by steel mills.

[0058] Calculation of timeliness requirements include: in, This refers to the actual transport time of the backup transport network chain. This represents the maximum acceptable delivery time required by steel mills.

[0059] Calculate dosage fit include: in, This represents the maximum cargo flow carrying capacity of the backup transport network chain. The total annual iron ore demand of the steel mills covered by the backup transport network chain.

[0060] For example, ≥0 indicates a perfect fit, 0.6≤ <0 indicates basic adaptation. A value less than 0.6 indicates insufficient adaptation, and the following differentiated technical optimization strategies should be implemented accordingly: A fully compatible backup transportation network: monitor the resource utilization rate of port nodes and review the compatibility indicators every six months. Basic-fit backup transportation network: Adjust the capacity allocation ratio and route channel combination to address deviations in route timeliness or category suitability; Inadequately adapted backup transportation networks: Initiate the network reconstruction process, readjust the selection of port nodes, matching of transportation channels, and steel mill docking schemes. If the basic adaptation standards still cannot be met after reconstruction, the reconstructed network will be withdrawn and replanned.

[0061] Specifically, when the network disturbance is an extreme disturbance, capacity is allocated to each of the backup transport network chains, including: in, For the first The capacity allocation of the aforementioned backup transport network chain. This refers to the total transport capacity that needs to be diverted from the core transport network when the network disturbance occurs. For the first The weight of each of the aforementioned backup transport network chains, For the first The average channel immunity of the aforementioned backup transport network chain, For the first The weight of each of the aforementioned backup transport network chains, For the first The average channel immunity of each of the aforementioned backup transport network chains.

[0062] Example 2 like Figure 2As shown, this embodiment proposes a port cluster iron ore transportation network construction and resilience planning optimization system that integrates intelligent decision-making, specifically including the following modules: The networking module is used to map all ports between the origin and destination of iron ore transportation as port nodes, and the channels between the port nodes are mapped as edges, forming multiple transportation network chains between the origin and the destination. The network chain segmentation module is used to divide each of the transport networks into core transport networks or backup transport networks based on the overall transport time, network chain disturbance rate and capacity utilization rate of each transport network, and to calculate the resilience value of each backup transport network. Among these, the core transport networks are preferentially selected for iron ore transport. The control module is used to calculate the comprehensive quantification value of the disturbance when the core transport network chain is disturbed, determine whether to activate the backup transport network chain, and select the corresponding backup transport network chain according to the resilience value if activated.

[0063] Since the system technical solution of this embodiment 2 is based on the technical solution of embodiment 1, it will not be described again.

[0064] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for constructing and optimizing the resilience planning of a port cluster iron ore transportation network chain integrating intelligent decision-making, characterized in that, include: All ports between the origin and destination of iron ore transportation are mapped as port nodes, and the channels between the port nodes are mapped as edges, forming multiple transportation network chains between the origin and the destination. Based on the overall transportation timeliness, chain disturbance rate, and capacity utilization rate of each transportation chain, each transportation chain is divided into a core transportation chain or a backup transportation chain, and the resilience value of each backup transportation chain is calculated. Among them, the core transportation chain is selected first for iron ore transportation, and the chain disturbance rate refers to the total frequency of chain disturbances within the statistical period. When the core transportation network chain is disturbed, the product of all disturbance quantification values ​​and their corresponding weights is summed to calculate the comprehensive disturbance quantification value of the network chain disturbance. It is then determined whether to activate the backup transportation network chain. If activated, the corresponding backup transportation network chain is selected based on the resilience value. The disturbance quantification value includes: the quantification value of the disturbance duration, the quantification value of the number of transportation channels affected, the quantification value of the amount of cargo delay, or the quantification value of the efficiency loss rate.

2. The method for constructing and optimizing the iron ore transportation network of port clusters based on intelligent decision-making as described in claim 1, characterized in that, Before forming multiple transportation networks from the origin to the destination, the method further includes: dividing each port node into a core hub port node, a regional transshipment port node, or a feeder port node. Each transportation network includes the core hub port node, the regional transshipment port node, and the feeder port node. Multiple evaluation indicators are set for each port node, normalized, and weights are assigned to each indicator to calculate a comprehensive evaluation value for each port node. The evaluation indicators include: an unloading scale indicator represented by the annual iron ore ocean-going vessel unloading volume; an intermodal transport suitability indicator represented by the ratio of intermodal transshipment cargo to the port's total annual iron ore transshipment volume; a transshipment timeliness indicator represented by the average iron ore transshipment time; a feeder capacity indicator represented by the annual feeder vessel unloading volume; and a delivery coverage indicator represented by the short-distance delivery radius.

3. The method for constructing and optimizing the resilience planning of a port cluster iron ore transportation network chain integrating intelligent decision-making as described in claim 2, characterized in that, The calculation of the comprehensive evaluation value for each of the port nodes includes: in, For the first The comprehensive evaluation value of each of the aforementioned port nodes, For the first The first port node The aforementioned evaluation indicators, For the first The first port node The weights of the evaluation indicators; when When the value is greater than or equal to the first evaluation threshold, the first evaluation threshold will be... The aforementioned port nodes are divided into the core hub port nodes, when When the value is less than the first evaluation threshold and greater than or equal to the second evaluation threshold, the first evaluation threshold will be... The aforementioned port nodes are divided into transit port nodes in the region, when When it is less than the second evaluation threshold, the first The port nodes are divided into the feed port nodes.

4. The method for constructing and optimizing the iron ore transportation network of port clusters based on integrated intelligent decision-making as described in claim 1, characterized in that, After forming multiple transport network chains between the origin and the destination, the method further includes: determining the number of transport network chains. in, The number of the transport network chains, This represents the total annual iron ore transport volume for all the aforementioned port nodes. For the first The maximum cargo flow carrying capacity of the aforementioned transportation network chain.

5. The method for constructing and optimizing the resilience planning of a port cluster iron ore transportation network chain integrating intelligent decision-making as described in claim 1, characterized in that, Based on the overall transportation timeliness, network disturbance rate, and capacity utilization rate of each transportation network chain, each transportation network chain is divided into a core transportation network chain or a backup transportation network chain, including: designating transportation network chains with a capacity utilization rate greater than or equal to a capacity utilization rate threshold as candidate core transportation network chains, and designating transportation network chains with a capacity utilization rate less than the capacity utilization rate threshold as candidate backup transportation network chains; If the overall transportation time of the candidate core transportation network chain is less than or equal to a first threshold for overall transportation time, and the network chain disturbance rate is less than or equal to a first threshold for network chain disturbance rate, then it is classified as the core transportation network chain; otherwise, it is classified as the backup transportation network chain. If the overall transportation time of the candidate backup transportation network chain is less than or equal to a second threshold for overall transportation time, the network chain disturbance rate is less than or equal to a second threshold for network chain disturbance rate, and the average time required for the candidate backup transportation network chain to recover to a preset percentage of its rated capacity after activation is less than or equal to a recovery time threshold, then the candidate backup transportation network chain is designated as the backup transportation network chain; otherwise, it is re-planned.

6. The method for constructing and optimizing the resilience planning of a port cluster iron ore transportation network chain integrating intelligent decision-making as described in claim 1, characterized in that, Calculating the resilience value of each of the aforementioned backup transport network chains includes: in, The toughness value, As the first weight, The weights are used to measure the robustness of the network. The robustness value of the backup transport network chain is given. As the weight of redundancy, This refers to the redundancy of core port nodes in the backup transportation network. As the weight of the channel immunity, This refers to the channel immunity of the channels between the port nodes in the backup transportation network chain. As the second weight, To restore the weight of the timeliness value, To restore the validity period, Weights for restoring efficiency, To restore efficiency, As a weight for emergency response efficiency, To improve emergency response efficiency, As the third weight, Weights for path switching adaptability. For path switching adaptability, Weighting of the response accuracy of capacity allocation To improve the accuracy of capacity allocation response, The weighting of capacity loss rate to maintain resilience To maintain resilience and reduce capacity loss rates, As the fourth weight, As a weight for resilience iteration efficiency, For resilient iteration efficiency, The weight of the perturbation experience utilization rate, To improve the utilization rate of perturbation experience, As a weight for the improvement rate of toughness assessment accuracy, To improve the accuracy of toughness assessment.

7. The method for constructing and optimizing the iron ore transportation network of port clusters based on intelligent decision-making as described in claim 1, characterized in that, Determining whether to activate the backup transport network chain includes: When the perturbation comprehensive quantization value If the disturbance value is less than the first disturbance threshold, the disturbance is considered a general disturbance, and only the capacity of the corresponding port node in the core transportation network is adjusted. If the disturbance value is greater than or equal to the first disturbance threshold and less than the second disturbance threshold, then the network chain disturbance is considered a major disturbance, and the core transport network chain is switched to the backup transport network chain. If the disturbance is greater than or equal to the second disturbance threshold, then the disturbance in the network chain is an extreme disturbance, and all the backup transport network chains are activated for coordinated operation.

8. The method for constructing and optimizing the resilience planning of a port cluster iron ore transportation network chain integrating intelligent decision-making as described in claim 7, characterized in that, The corresponding backup transport network chain selected based on the resilience value includes: in, This is a toughness correction value. The toughness value, The weight of the toughness value, The adaptation evaluation value for the backup transport network chain; When the disturbance in the network chain is a major disturbance, the core transport network chain is switched to the backup transport network chain corresponding to the largest resilience correction value among all the backup transport network chains.

9. The method for constructing and optimizing the resilience planning of a port cluster iron ore transportation network chain integrating intelligent decision-making as described in claim 7, characterized in that, When the disturbance in the transport network is an extreme disturbance, capacity is allocated to each of the backup transport networks, including: in, For the first The capacity allocation of the aforementioned backup transport network chain. This refers to the total transport capacity that needs to be diverted from the core transport network when the network disturbance occurs. For the first The weight of each of the aforementioned backup transport network chains, For the first The average channel immunity of the aforementioned backup transport network chain, For the first The weight of each of the aforementioned backup transport network chains, For the first The average channel immunity of each of the aforementioned backup transport network chains.

10. A port cluster iron ore transportation network construction and resilience planning optimization system integrating intelligent decision-making, characterized in that, include: The networking module is used to map all ports between the origin and destination of iron ore transportation as port nodes, and the channels between the port nodes are mapped as edges, forming multiple transportation network chains between the origin and the destination. The network chain segmentation module is used to divide each of the transport networks into core transport networks or backup transport networks based on the overall transport time, network chain disturbance rate, and capacity utilization rate of each transport network chain, and to calculate the resilience value of each backup transport network chain. The core transport network chain is selected first for iron ore transport. The network chain disturbance rate refers to the total frequency of network chain disturbances within the statistical period. The control module is used to sum all disturbance quantification values ​​and their corresponding weighted products when the core transportation network chain is disturbed, calculate the comprehensive disturbance quantification value of the network chain disturbance, determine whether to activate the backup transportation network chain, and if activated, select the corresponding backup transportation network chain according to the resilience value. The disturbance quantification value includes: the quantification value of the disturbance duration, the quantification value of the number of transportation channels affected, the quantification value of the amount of cargo delay, or the quantification value of the efficiency loss rate.

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